Natural Microbial Communities Research Articles

How bioaugmentation for pesticide removal influences the microbial community in biologically active sand filters

Removing pesticides from biological drinking water filters is challenging due to the difficulty in activating pesticide-degrading bacteria within the filters. Bioaugmented bacteria can alter the filter's microbiome, affecting its performance either positively or negatively, depending on the bacteria used and their interaction with native microbes. We demonstrate that adding specific bacteria strains can effectively remove recalcitrant pesticides, like metaldehyde, yielding compliance to regulatory standards for an extended period. Our experiments revealed that the Sphingobium CMET-H strain was particularly effective, consistently reducing metaldehyde concentrations to levels within regulatory compliance, significantly outperforming Acinetobacter calcoaceticus E1. This success is attributed to the superior acclimation and distribution of the Sphingobium strain within the filter bed, facilitating more efficient interactions with and degradation of the pesticide, even when present at lower population densities compared to Acinetobacter calcoaceticus E1. Furthermore, our study demonstrates that the addition of pesticide-degrading strains significantly impacts the filter's microbiome at various depths, despite these strains making up less than 1% of the total microbial community. The sequence in which these bacteria are introduced influences the system's ability to degrade pesticides effectively. This research shows the potential of carefully selected and dosed bioaugmented bacteria to improve the pesticide removal capabilities of water filtration systems, while also highlighting the dynamics between bioaugmented and native microbial communities. Further investigation into optimizing bioaugmentation strategies is suggested to enhance the resilience and efficiency of drinking water treatment systems against pesticide contamination.

Persistent enrichment of multidrug-resistant Klebsiella in oral and nasal communities during long-term starvation

BackgroundThe human oral and nasal cavities can act as reservoirs for opportunistic pathogens capable of causing acute infection. These microbes asymptomatically colonize the human oral and nasal cavities which facilitates transmission within human populations via the environment, and they routinely possess clinically significant antibiotic resistance genes. Among these opportunistic pathogens, the Klebsiella genus stands out as a notable example, with its members frequently linked to nosocomial infections and multidrug resistance. As with many colonizing opportunistic pathogens, the essential transmission factors influencing the spread of Klebsiella species among both healthy and diseased individuals remain unclear.ResultsHere, we explored a possible explanation by investigating the ability of oral and nasal Klebsiella species to outcompete their native microbial community members under in vitro starvation conditions, which could be analogous to external hospital environments or the microenvironment of mechanical ventilators. When K. pneumoniae and K. aerogenes were present within a healthy human oral or nasal sample, the bacterial community composition shifted dramatically under starvation conditions and typically became enriched in Klebsiella species. Furthermore, introducing K. pneumoniae exogenously into a native microbial community lacking K. pneumoniae, even at low inoculum, led to repeated enrichment under starvation. Precise monitoring of K. pneumoniae within these communities undergoing starvation indicated rapid initial growth and prolonged viability compared to other members of the microbiome. K. pneumoniae strains isolated from healthy individuals’ oral and nasal cavities also exhibited resistance to multiple classes of antibiotics and were genetically similar to clinical and gut isolates. In addition, we found that in the absence of Klebsiella species, other understudied opportunistic pathogens, such as Peptostreptococcus, increased in relative abundance under starvation conditions.ConclusionsOur findings establish an environmental and microbiome community circumstance that allows for the enrichment of Klebsiella species and other opportunistic pathogens. Klebsiella’s enrichment may hinge on its ability to quickly outgrow other members of the microbiome. The ability to outcompete other commensal bacteria and to persist under harsh environmental conditions could be an important factor that contributes to enhanced transmission in both commensal and pathogenic contexts.2NMbQE6jVjinwr48dC_rNoVideo

Green spaces contribute to structural resilience of the gut microbiota in urban mammals

The gut microbiome of wild animals is subject to various environmental influences, including those associated with human-induced alterations to the environment. We investigated how the gut microbiota of a synurbic rodent species, the striped field mouse (Apodemus agrarius), change in cities of varying sizes, seeking the urban microbiota signature for this species. Fecal samples for analysis were collected from animals living in non-urbanized areas and green spaces of different-sized cities (Poland). Metagenomic 16S rRNA gene sequencing and further bioinformatics analyses were conducted. Significant differences in the composition of gut microbiomes among the studied populations were found. However, the observed changes were dependent on local habitat conditions, without strong evidence of a correlation with the size of the urbanized area. The results suggest that ecological detachment from a more natural, non-urban environment does not automatically lead to the development of an “urban microbiome” model in the studied rodent. The exposure to the natural environment in green spaces may serve as a catalyst for microbiome transformations, providing a previously underestimated contribution to the maintenance of native gut microbial communities in urban mammals.

The impact of DNA extraction on the quantification of Legionella, with implications for ecological studies.

Monitoring the levels of opportunistic pathogens in drinking water is important to plan interventions and understand the ecological niches that allow them to proliferate. Quantitative PCR is an established alternative to culture methods that can provide a faster, higher-throughput, and more precise enumeration of the bacteria in water samples. However, PCR-based methods are still not routinely applied for Legionella monitoring, and techniques, such as DNA extraction, differ notably between laboratories. Here, we quantify the impact that DNA extraction methods had on downstream PCR quantification and community sequencing. Through a community science campaign, we collected 50 water samples and corresponding shower hoses, and compared two commonly used DNA extraction methodologies to the same biofilm and water phase samples. The two methods showed clearly different extraction efficacies, which were reflected in both the quantity of DNA extracted and the concentrations of Legionella enumerated in both the matrices. Notably, one method resulted in higher enumeration in nearly all samples by about one order of magnitude and detected Legionella in 21 samples that remained undetected by the other method. 16S rRNA amplicon sequencing revealed that the relative abundance of individual taxa, including sequence variants of Legionella, significantly varied depending on the extraction method employed. Given the implications of these findings, we advocate for improvement in documentation of the performance of DNA extraction methods used in drinking water to detect and quantify Legionella, and characterize the associated microbial community.IMPORTANCEMonitoring for the presence of the waterborne opportunistic pathogen Legionella is important to assess the risk of infection and plan remediation actions. While monitoring is traditionally carried on through cultivation, there is an ever-increasing demand for rapid and high-throughput molecular-based approaches for Legionella detection. This paper provides valuable insights on how DNA extraction affects downstream molecular analysis such as the quantification of Legionella through droplet digital PCR and the characterization of natural microbial communities through sequencing analysis. We analyze the results from a risk-assessment, legislative, and ecological perspective, showing how initial DNA processing is an important step to take into account when shifting to molecular-based routine monitoring and discuss the central role of consistent and detailed reporting of the methods used.

Metabolic complexity drives divergence in microbial communities.

Microbial communities are shaped by environmental metabolites, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. Here we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but they diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively simpler ones that then participate in cross-feeding between community members, is necessary and sufficient to recapitulate our experimental observations. In addition to helping understand the role of the environment in community assembly, the divergence-complexity effect can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions towards microbiome engineering applications.

Design and analysis of quorum sensing language “Interpreter” ecosystem for microbial community

Microbes in diverse natural communities communicate via quorum sensing (QS) signals that act as microbial languages. QS-based communications have been reconstructed in two-strain microbiota for promising consortium-based applications. However, investigation and synthesis of multiple QS signals transmission in the QS communication network (QSCN) are less explored. In this study, QS language “interpreter” was proposed and constructed in five Escherichia coli strains to simulate the linear and circular QSCN among natural microbial communities. Specifically, by combining strain-level microscopic and bulk-level macroscopic measurements, we investigate the performances and dynamics of synthetic three-strain QS language “interpreter” ecosystems that are in response to dramatic environmental changes. Results of micro- and macroscopic experiments showed that the existence of complex QS language “interpreter” ecosystems promote the stability maintenance of microbial community. Furthermore, a comprehensive kinetic computational model was developed for the optimization of tunable directed QSCN. Finally, the perspectives of the QSCN for the effective control of microbial communities were discussed and summarized. This study revealed the dynamic control of complex microbial communications, contributing to ecosystem-based engineering and microbiome-based therapeutics.

Influence of an indigenous yeast, CECA, from the Ningxia wine region of China, on the fungal and bacterial dynamics and function during Cabernet Sauvignon wine fermentation.

Saccharomyces cerevisiae CECA was a potential indigenous Chinese wine yeast that can produce aroma and flavor in Cabernet Sauvignon wines. High-throughput sequencing combined with metabolite analysis was applied to analyze the effects of CECA inoculation on the native microbial community interaction and metabolism during Cabernet Sauvignon wine fermentation. Fermentations were performed with three different inoculant strategies: spontaneous fermentation without inoculation, inoculation with CECA after grape must sterilization, and direct inoculation of CECA. Results showed that the diversity of bacteria (P = 0.033) is more sensitive to CECA inoculation than fungi (P = 0.563). In addition, CECA inoculation altered the species composition of core microorganisms (relative abundance >1%) and the keystone species (accounting for the top 1% of the most important interactions), as well as of the biomarkers (linear discriminant analysis > 3.0, P < 0.05). Furthermore, the inoculation could change the cluster of metabolites, and these differential metabolite sets were correlated with four fungal taxa of Issatchenkia, Issatchenkia orientalis, Saccharomycetales, Saccharomycetes and two bacterial taxa of Pantoea, Tatumella ptyseos, were significantly correlated. Inoculated fermentation also altered the correlation between dominant microorganisms and aroma compounds, giving Cabernet Sauvignon wines more herbal, floral, fruity, and cheesy aromas. Saccharomyces cerevisiae CECA and dimethyl dicarbonate (DMDC) inhibition treatments significantly altered the microbial community structure of Cabernet Sauvignon wines, which in turn affected the microbial-metabolite correlation. These findings will help winemakers to control the microbial dynamics and functions during wine fermentation, and be more widely used in regional typical wine fermentations. © 2024 Society of Chemical Industry.

Silicon Fertilization Improves Sunflower Rhizosphere Microbial Community Structure and Reduces Parasitism by Orobanche cumana Wallr.

Sunflower broomrape (Orobanche cumana Wallr.) has severely restricted the development of the sunflower industry in China, and more efficient and convenient control methods are urgently needed. In this experiment, we investigated the effects of N, P and silica fertilizers on the parasitism rate of O. cumana, as well as on the yield of sunflower and native microbial communities in the field. Firstly, pot experiments were conducted to select the most effective fertilization method and to determine the physiological and biochemical indexes of sunflowers. Subsequently, field application studies were carried out to determine the physiological indexes, yield, O. cumana parasitism on sunflower, and the effect on the indigenous microbial community. The results demonstrate that compared with the CNP treatment (Control), the number of parasites under the N1P5 treatment significantly decreased by 66.15%. The exogenous application of silica can significantly reduce the number of O. cumana parasites. The treatments with N1P5 (N/P = 1:5) and available SiO2 content higher than 40 mg/kg (NS2, NS3, SF2 and SF3) significantly increased superoxide dismutase (SOD) activity and decreased malondialdehyde (MDA) content in sunflower leaves. In the field, fertilization significantly decreased the number of O. cumana parasites. The S treatment improved the native microbial community structure and enriched beneficial microorganisms, including Vicinamibacteria and Pyrinomonadaceae. Additionally, applying the S treatment significantly increased sunflower yield by 23.82% and crude protein content by 20.20%. In summary, the application of silicon fertilizer can effectively improve the host microbial community, reduce O. cumana parasitism and improve the yield and quality of sunflower.

Predicting the First Steps of Evolution in Randomly Assembled Communities.

Microbial communities can self-assemble into highly diverse states with predictable statistical properties. However, these initial states can be disrupted by rapid evolution of the resident strains. When a new mutation arises, it competes for resources with its parent strain and with the other species in the community. This interplay between ecology and evolution is difficult to capture with existing community assembly theory. Here, we introduce a mathematical framework for predicting the first steps of evolution in large randomly assembled communities that compete for substitutable resources. We show how the fitness effects of new mutations and the probability that they coexist with their parent depends on the size of the community, the saturation of its niches, and the metabolic overlap between its members. We find that successful mutations are often able to coexist with their parent strains, even in saturated communities with low niche availability. At the same time, these invading mutants often cause extinctions of metabolically distant species. Our results suggest that even small amounts of evolution can produce distinct genetic signatures in natural microbial communities.

Responses of soil microbial diversity, network complexity and multifunctionality to environments changes in volcanic ecosystems

Volcanic ecosystems with unique and reduced-complexity environments are distributed globally, providing a platform for analysing the structure and function of natural microbial communities. This study aimed to explore the responses of soil microbial diversity, network complexity, and multifunctionality to environments changes in volcanic ecosystems. Actinobacteria (26.00–46.26 %), Acidobacteriota (5.68–19.10 %), and Crenarchaeota (4.71–18.65 %) were the dominant prokaryotic phyla. Furthermore, bacterial community was dominant over archaeal community. Among the fungal phyla, Ascomycota accounted for 60.30–94.45 % of the relative abundance. Fungal communities were more sensitive to the changes in biogeographical patterns in volcanic soils, while the prokaryotic community was more diverse. There were more biomarkers and functional compositions at the bottom of volcano sites than at the top (biomarkers: 85 vs. 39; functional group: 18 vs. 2; ecological guild: 8:1). The networks at the bottom of volcano had an increased complexity and connectivity (higher avgK and avgCC; shorter GD). The network in the top volcano was highly modularised. Three keystone species were observed only in this network. Soil chemical factors, directly and indirectly, influenced microbial structure and multifunctionality. Therefore, this study may provide key insights into understanding the assemblage of soil microbial communities in extreme environments, such as volcanic areas.

Anthropogenic pollution may enhance natural transformation in water, favouring the spread of antibiotic resistance genes

Aquatic ecosystems are crucial in the antimicrobial resistance cycle. While intracellular DNA has been extensively studied to understand human activity's impact on antimicrobial resistance gene (ARG) dissemination, extracellular DNA is frequently overlooked. This study examines the effect of anthropogenic water pollution on microbial community diversity, the resistome, and ARG dissemination. We analyzed intracellular and extracellular DNA from wastewater treatment plant effluents and lake surface water by shotgun sequencing. We also conducted experiments to evaluate anthropogenic pollution's effect on transforming extracellular DNA (using Gfp-plasmids carrying ARGs) within a natural microbial community. Chemical analysis showed treated wastewater had higher anthropogenic pollution-related parameters than lake water. The richness of microbial community, antimicrobial resistome, and high-risk ARGs was greater in treated wastewaters than in lake waters both for intracellular and extracellular DNA. Except for the high-risk ARGs, richness was significantly higher in intracellular than in extracellular DNA. Several ARGs were associated with mobile genetic elements and located on plasmids. Furthermore, Gfp-plasmid transformation within a natural microbial community was enhanced by anthropogenic pollution levels. Our findings underscore anthropogenic pollution's pivotal role in shaping microbial communities and their antimicrobial resistome. Additionally, it may facilitate ARG dissemination through extracellular DNA plasmid uptake.

A systematic comparison of natural product potential, with an emphasis on RiPPs, by mining of bacteria of three large ecosystems

The implementation of several global microbiome studies has yielded extensive insights into the biosynthetic potential of natural microbial communities. However, studies on the distribution of several classes of ribosomally synthesized and post-translationally modified peptides (RiPPs), non-ribosomal peptides (NRPs) and polyketides (PKs) in different large microbial ecosystems have been very limited. Here, we collected a large set of metagenome-assembled bacterial genomes from marine, freshwater and terrestrial ecosystems to investigate the biosynthetic potential of these bacteria. We demonstrate the utility of public dataset collections for revealing the different secondary metabolite biosynthetic potentials among these different living environments. We show that there is a higher occurrence of RiPPs in terrestrial systems, while in marine systems, we found relatively more terpene-, NRP-, and PK encoding gene clusters. Among the many new biosynthetic gene clusters (BGCs) identified, we analyzed various Nif-11-like and nitrile hydratase leader peptide (NHLP) containing gene clusters that would merit further study, including promising products, such as mersacidin-, LAP- and proteusin analogs. This research highlights the significance of public datasets in elucidating the biosynthetic potential of microbes in different living environments and underscores the wide bioengineering opportunities within the RiPP family.

A multi-step approach: Coupling of biodegradation and UV photocatalytic oxidation TiO2 for the treatment of naphthenic acid fraction compounds in oil sands process-affected water

Bitumen extraction in Alberta's oil sands region uses large volumes of water, leading to an abundance of oil sands process-affected water (OSPW). OSPW contains naphthenic acid fraction compounds (NAFCs) which have been found to contribute to OSPW toxicity. This study utilized a multistep treatment, coupling biological degradation with UV photocatalytic oxidation, and nutrient addition to boost the native microbial community's degradation capacity. OSPW initially contained 40–42 mg/L NAFCs with a toxicity of 3.8–3.9 TU. Initial biodegradation (Step 1) was used to remove the easily biodegradable NAFCs (11–25% removal), followed by a light or heavy dose of oxidation (Step 2) to breakdown the recalcitrant NAFCs (66–82% removal). Lastly, post-oxidation biodegradation with nutrients (Step 3) removed the residual bioavailable NAFCs (16–31% removal). By the end of the multistep treatment, the final NAFC concentrations and toxicity ranged from 5.3 to 6.8 mg/L and 1.1–1.2 TU. Analysis showed that OPSW was limited in phosphorus (below detection limit), and the addition of nutrients improved the degradation of NAFCs. Two treatments throughout the multistep treatment never received nutrients and showed minimal NAFC degradation post-oxidation. The native microbial community survived the stress from UV photocatalytic oxidation as seen by the post-oxidation NAFC biodegradation. Microbial community diversity was reduced considerably following oxidation, but increased with nutrient addition. The microbial community consisted predominately of Proteobacteria (Gammaproteobacteria and Alphaproteobacteria), and the composition shifted depending on the level of oxidation received. Possible NAFC-degrading microbes identified after a light oxidation dose included Pseudomonas, Acinetobacter and Xanthomonadales, while Xanthobacteracea and Rhodococcus were the dominant microbes after heavy oxidation. This experiment confirms that the microbial community is capable of degrading NAFCs and withstanding oxidative stress, and that degradation is further enhanced with the addition of nutrients.

Environmental activity-based protein profiling for function-driven enzyme discovery from natural communities

BackgroundMicrobial communities are important drivers of global biogeochemical cycles, xenobiotic detoxification, as well as organic matter decomposition. Their major metabolic role in ecosystem functioning is ensured by a unique set of enzymes, providing a tremendous yet mostly hidden enzymatic potential. Exploring this enzymatic repertoire is therefore not only relevant for a better understanding of how microorganisms function in their natural environment, and thus for ecological research, but further turns microbial communities, in particular from extreme habitats, into a valuable resource for the discovery of novel enzymes with potential applications in biotechnology. Different strategies for their uncovering such as bioprospecting, which relies mainly on metagenomic approaches in combination with sequence-based bioinformatic analyses, have emerged; yet accurate function prediction of their proteomes and deciphering the in vivo activity of an enzyme remains challenging.ResultsHere, we present environmental activity-based protein profiling (eABPP), a multi-omics approach that extends genome-resolved metagenomics with mass spectrometry-based ABPP. This combination allows direct profiling of environmental community samples in their native habitat and the identification of active enzymes based on their function, even without sequence or structural homologies to annotated enzyme families. eABPP thus bridges the gap between environmental genomics, correct function annotation, and in vivo enzyme activity. As a showcase, we report the successful identification of active thermostable serine hydrolases from eABPP of natural microbial communities from two independent hot springs in Kamchatka, Russia.ConclusionsBy reporting enzyme activities within an ecosystem in their native state, we anticipate that eABPP will not only advance current methodological approaches to sequence homology-guided enzyme discovery from environmental ecosystems for subsequent biocatalyst development but also contributes to the ecological investigation of microbial community interactions by dissecting their underlying molecular mechanisms.

Dynamic Succession of Natural Microbes during the Ecolly Grape Growth under Extremely Simplified Eco-Cultivation.

The composition and continuous succession of natural microbial communities during grape growth play important roles in grape health and flavor quality as well as in characterizing the regional wine terroir. This study explored the diversity and dynamics of fruit epidermal microbes at each growth and developmental stage of Ecolly grapes under an extremely simplified eco-cultivation model, analyzed microbial interactions and associations of weather parameters to specific communities, and emphasized metabolic functional characteristics of microecology. The results indicated that the natural microbial community changed significantly during the grape growth phase. The dominant fungal genera mainly included Gibberella, Alternaria, Filobasidium, Naganishia, Ascochyta, Apiotrichum, Comoclathris, and Aureobasidium, and the dominant bacterial genera mainly contained Sediminibacterium, Ralstonia, Pantoea, Bradyrhizobium, Brevundimonas, Mesorhizobium, Planococcus, and Planomicrobium. In summary, filamentous fungi gradually shifted to basidiomycetous yeasts along with fruit ripening, with a decline in the number of Gram-negative bacteria and a relative increase in Gram-positive bacteria. The community assembly process reflects the fact that microbial ecology may be influenced by a variety of factors, but the fungal community was more stable, and the bacterial community fluctuated more from year to year, which may reflect their response to weather conditions over the years. Overall, our study helps to comprehensively profile the ecological characteristics of the grape microbial system, highlights the natural ecological viticulture concept, and promotes the sustainable development of the grape and wine industry.

Tuning interdomain conjugation to enable in situ population modification in yeasts.

The ability to modify and control natural and engineered microbiomes is essential for biotechnology and biomedicine. Fungi are critical members of most microbiomes, yet technology for modifying the fungal members of a microbiome has lagged far behind that for bacteria. Interdomain conjugation (IDC) is a promising approach, as DNA transfer from bacterial cells to yeast enables in situ modification. While such genetic transfers have been known to naturally occur in a wide range of eukaryotes and are thought to contribute to their evolution, IDC has been understudied as a technique to control fungal or fungal-bacterial consortia. One major obstacle to the widespread use of IDC is its limited efficiency. In this work, we manipulated metabolic and physical interactions between genetically tractable Escherichia coli and Saccharomyces cerevisiae to control the incidence of IDC. We test the landscape of population interactions between the bacterial donors and yeast recipients to find that bacterial commensalism leads to maximized IDC, both in culture and in mixed colonies. We demonstrate the capacity of cell-to-cell binding via mannoproteins to assist both IDC incidence and bacterial commensalism in culture and model how these tunable controls can predictably yield a range of IDC outcomes. Furthermore, we demonstrate that these controls can be utilized to irreversibly alter a recipient yeast population, by both "rescuing" a poor-growing recipient population and collapsing a stable population via a novel IDC-mediated CRISPR/Cas9 system.IMPORTANCEFungi are important but often unaddressed members of most natural and synthetic microbial communities. This work highlights opportunities for modifying yeast microbiome populations through bacterial conjugation. While conjugation has been recognized for its capacity to deliver engineerable DNA to a range of cells, its dependence on cell contact has limited its efficiency. Here, we find "knobs" to control DNA transfer, by engineering the metabolic dependence between bacterial donors and yeast recipients and by changing their ability to physically adhere to each other. Importantly, we functionally validate these "knobs" by irreversibly altering yeast populations. We use these controls to "rescue" a failing yeast population, demonstrate the capacity of conjugated CRISPR/Cas9 to depress or collapse populations, and show that conjugation can be easily interrupted by disrupting cell-to-cell binding. These results offer building blocks toward in situ mycobiome editing, with significant implications for clinical treatments of fungal pathogens and other fungal system engineering.

Microbial response to a port fuel spill: Community dynamics and potential for bioremediation

Following a fuel leakage inside a Portuguese maritime port, we conducted parallel 30-day experiments using contaminated seawater and fuel, sampled five days after the incident. This study aimed to (i)survey the native microbial community response to the spilled fuel and (ii)evaluate the efficacy of bioremediation, both biostimulation and bioaugmentation with a lyophilized bacterial consortium (Rhodococcus erythropolis, Pseudomonas sp.), in accelerating hydrocarbon degradation. Metabarcoding analysis revealed a shift in microbial communities, with increased abundance of hydrocarbon-degraders (e.g. Alcanivorax, Thalassospira). Ninety-five hydrocarbonoclastic bacteria were isolated, including key groups from the enriched communities. The lyophilized bacteria added in bioaugmentation, enhanced the abundance of hydrocarbon-degraders over time and were recovered throughout time. Bioremediation treatments favoured biodegradation, achieving over 60 % removal of total petroleum hydrocarbons after 15 days, contrasting with natural attenuation where almost no TPH was removed. This work highlights the potential of bioremediation technologies to accelerate hydrocarbon-degrading activity, for oil spills inside ports.

Kinetics-based inference of environment-dependent microbial interactions and their dynamic variation.

Microbial communities in nature are dynamically evolving as member species change their interactions subject to environmental variations. Accounting for such context-dependent dynamic variations in interspecies interactions is critical for predictive ecological modeling. In the absence of generalizable theoretical foundations, we lack a fundamental understanding of how microbial interactions are driven by environmental factors, significantly limiting our capability to predict and engineer community dynamics and function. To address this issue, we propose a novel theoretical framework that allows us to represent interspecies interactions as an explicit function of environmental variables (such as substrate concentrations) by combining growth kinetics and a generalized Lotka-Volterra model. A synergistic integration of these two complementary models leads to the prediction of alterations in interspecies interactions as the outcome of dynamic balances between positive and negative influences of microbial species in mixed relationships. The effectiveness of our method was experimentally demonstrated using a synthetic consortium of two Escherichia coli mutants that are metabolically dependent (due to an inability to synthesize essential amino acids) but competitively grow on a shared substrate. The analysis of the E. coli binary consortium using our model not only showed how interactions between the two amino acid auxotrophic mutants are controlled by the dynamic shifts in limiting substrates but also enabled quantifying previously uncharacterizable complex aspects of microbial interactions, such as asymmetry in interactions. Our approach can be extended to other ecological systems to model their environment-dependent interspecies interactions from growth kinetics.IMPORTANCEModeling environment-controlled interspecies interactions through separate identification of positive and negative influences of microbes in mixed relationships is a new capability that can significantly improve our ability to understand, predict, and engineer the complex dynamics of microbial communities. Moreover, the prediction of microbial interactions as a function of environmental variables can serve as valuable benchmark data to validate modeling and network inference tools in microbial ecology, the development of which has often been impeded due to the lack of ground truth information on interactions. While demonstrated against microbial data, the theory developed in this work is readily applicable to general community ecology to predict interactions among macroorganisms, such as plants and animals, as well as microorganisms.

Fungal communities are passengers in community development of dune ecosystems, while bacteria are not.

An increasing number of studies of above-belowground interactions provide a fundamental basis for our understanding of the coexistence between plant and soil communities. However, we lack empirical evidence to understand the directionality of drivers of plant and soil communities under natural conditions: 'Are soil microorganisms driving plant community functioning or do they adapt to the plant community?' In a field experiment in an early successional dune ecosystem, we manipulated soil communities by adding living (i.e., natural microbial communities) and sterile soil inocula, originating from natural ecosystems, and examined the annual responses of soil and plant communities. The experimental manipulations had a persistent effect on the soil microbial community with divergent impacts for living and sterile soil inocula. The plant community was also affected by soil inoculation, but there was no difference between the impacts of living and sterile inocula. We also observed an increasing convergence of plant and soil microbial composition over time. Our results show that alterations in soil abiotic and biotic conditions have long-term effects on the composition of both plant and soil microbial communities. Importantly, our study provides direct evidence that soil microorganisms are not "drivers" of plant community dynamics. We found that soil fungi and bacteria manifest different community assemblies in response to treatments. Soil fungi act as "passengers," that is, soil microorganisms reflect plant community dynamics but do not alter it, whereas soil bacteria are neither "drivers" nor "passengers" of plant community dynamics in early successional ecosystems. These results are critical for understanding the community assembly of plant and soil microbial communities under natural conditions and are directly relevant for ecosystem management and restoration.

Plasmid size determines adsorption to clay and breakthrough in a saturated sand column

Horizontal gene transfer (HGT) is a major factor in the spread of antibiotic resistant genes (ARG). Transformation, one mode of HGT, involves the acquisition and expression of extracellular DNA (eDNA). eDNA in soils is degraded rapidly by extracellular nucleases. However, if bound to a clay particle, eDNA can persist for long periods of time without losing its transformation ability. To better understand the mechanism of eDNA persistence in soil, this experiment assessed the effects of 1) clay mineralogy, 2) mixed salt solution, 3) plasmid size on DNA adsorption to clay and 4) breakthrough behavior of three differently sized plasmids in an environmentally relevant solution. Batch test methods were used to determine adsorption trends of three differently sized DNA plasmids, pUC19, pBR322, and pTYB21, to several pure clay minerals, goethite (α-FeOOH), illite, and kaolinite, and one environmental soil sample. Results show not all sorbents have equal adsorption capacity based on surface area with adsorption capacities decreasing from goethite > illite = kaolinite > bulk soil, and low ionic strength solutions will likely not significantly alter sorption trends. Additionally, plasmid DNA size (i.e., length) was shown to be a significant predictor of adsorption efficiency and that size affects DNA breakthrough, with breakthroughs occurring later with larger plasmids. Given that DNA persistence is linked to its adsorption to soil constituents and breakthrough, eDNA size is likely an important contributor to the spread of ARG within natural microbial communities.